What the data for this category looks like
Typical data subjects for this category include game publishing compliance teams, content reviewers, and game producers. Daily processed documents fall into four categories: content self-check lists, sensitive content modification records, user agreements, and compliance review minutes. Data sources cover game story scripts, in-game text, art resource supporting instructions, and publicly released regulatory compliance requirements. Documents mostly use mixed formats, including structured tables, plain text paragraphs, and PDF embedded annotations. Fields include content title, review status, modification notes, and corresponding regulatory clauses. Update frequency is once per version or event cycle.
What constraints these characteristics impose on document parsing and chunking
Mixed-format compliance documents require parsing to extract structured tables and PDF annotations, to avoid missing key review information. High-frequency updates per version or event require chunking logic to support incremental parsing after partial content changes, to avoid wasting resources on full re-parsing. The long text attribute of game scripts and text requires chunk thresholds to match the associated length of regulatory clauses and corresponding game content, to avoid breaking associated information during splitting. Timeliness of document updates requires controlling single-file parsing duration to align with version launch schedules, to avoid delays caused by parsing timeouts.
How to set configurations
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the associated length of regulatory clauses and corresponding game content in compliance documents, to avoid breaking associated information during splitting |
chunkSplitter | Split by paragraph + title | Aligns with the structure of compliance documents categorized by review nodes and regulatory clauses, to retain contextual associations |
customPdfParse | Enabled | Supports parsing PDF embedded annotations and table content in compliance review minutes, to adapt to compliance document formats for art resource supporting materials |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to full compliance document packages updated per version, to avoid upload failures due to oversized files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Meets parsing duration requirements for multi-format mixed documents, to avoid parsing timeouts before version launches |
chunkSettingMode | Manual configuration | Adjusts chunking rules for the special structure of compliance documents, to adapt to different types of self-check documents |
Three common errors
- After uploading a compliance document package, the interface shows an abnormal number of chunks, and some chunk statuses show vectorization failure. Repeated retries only occasionally resolve the issue. Cause: The
chunkSizeparameter is not adjusted. An overly small chunk threshold creates a large number of fragmented chunks, increasing the load on the vectorization node. - After using a DB node to query a compliance database, the returned JSON or JSON array cannot be used directly for interface Q&A. Additional code conversion is required. Cause: Parsing rules adapted for structured data are not configured. The default parsing logic cannot automatically recognize non-text format data returned by databases.
- When parsing compliance review minutes, PDF embedded table annotation content is lost. Cause: The
customPdfParseconfiguration is not enabled. The default parsing logic does not extract supplementary content embedded in PDFs.
How to confirm configurations are correct
- Upload a single typical compliance document, review the parsed chunk results, and confirm that content associations are not broken during splitting.
- Test the linkage between the database query node and the Q&A interface, and confirm that returned structured data can be directly processed by the Q&A logic.
- Upload a compliance document containing tables and annotations, and check if parsed chunks retain original formatting and supplementary content.
- After adjusting chunk-related configurations, re-upload a large file, and confirm that the parsing process has no timeouts or abnormal errors.
The values provided are common starting points, and should be evaluated against the user's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.